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关键词： 伸缩缝   施工技术   市政路桥   运用  

摘要： 市政路桥工程是我国城市基础设施建设中的重点项目,随着我国城市化的建设与发展,市政路桥工程得到了充分的建设。市政路桥工程的质量和性能与城市交通存在着直接的关联,为了提高市政道路桥梁的施工水平,就要采取伸缩缝技术,通过伸缩缝维护路桥结构的整体性与稳定性,充分发挥伸缩缝在市政路桥施工中的应用作用。

关键词： 市政工程   桥梁   伸缩缝   防水控制   技术措施分析  

摘要： 现如今,公路桥梁伸缩缝混凝土裂缝现象较为显著,市政桥梁构建期间材料的属性以及热胀冷缩功能极为重要,伸缩缝防水性可以在很大程度上影响到桥梁功能的发挥,因此在日积月累之下,产生一系列质量问题如混凝土裂缝、伸缩缝变形、混凝土掉落、坑槽等问题,从而不利于行车的安全,而且也相应地增添了养护维修的费用支出。基于此,本文对市政道路桥梁工程项目施工中伸缩缝技术的主要作用、现阶段影响公路桥梁伸缩缝施工质量的因素以及市政桥梁伸缩缝防水控制的措施进行了分析。

关键词： 道路桥梁施工   伸缩缝   施工技术  

摘要： 伸缩缝是桥梁工程施工的最后工序,其质量管理应以结构耐久性和行车顺适性为总体目标,优选原材料与施工队伍,扎实落实首件制,以合理的施工组织,细化的过程控制,严格的现场检测工作及量化指标对工程质量进行过程和成品验收。

关键词： 市政道路桥梁工程   伸缩缝   施工质量  

摘要： 目前,我国市政道路在进行施工的时候,伸缩缝技术有着十分重要的意义。虽然伸缩缝技术施工的规模并不大,在整体的施工中比例较小,但是对于车辆的荷载作用却有直接的接触,十分容易受到破坏。一旦破坏之后,市政道路的防水性以及车辆运行的舒适度都会受到较大的影响。所以相关部门工作人员需要加强对伸缩缝技术的重视,提高伸缩缝的质量,从而延长市政道路的使用寿命,提高工程的质量。基于此,本文主要围绕着市政道路桥梁工程伸缩缝施工展开相关研究,供参考。

关键词： Peptides and proteins   Genetics   Protein dynamics   Rodent models   Inhibition   Oxidative stress  

摘要： The herbicide paraquat (PQ) induces hippocampal neuronal cell loss and cognitive dysfunction after one and repeated treatment. All the mechanisms involved in these effects are not well understood. Single and repeated PQ treatment increased A beta and tau protein levels, through HSP70 and TFEB downregulation and proteasome 20S inhibition, producing cell death in primary hippocampal neurons associated with cognitive decline. Our results reveal the mechanisms through which PQ could induce the accumulation of abnormal proteins and neurodegeneration that could originate the cognitive decline produced by it and could help managing its degenerative effects.

关键词： Bisphenol A   4-Methyl-2,4-bis(4-hydroxyphenyl)pent-1-ene   Neurotoxicity   Apoptosis   Mitochondria   ER stress   ERK1/2   Akt  

摘要： Bisphenol A (BPA) is recognized as a harmful pollutant in the worldwide. Growing studies have reported that BPA can cause adverse effects and diseases in human, and link to a potential risk factor for development of neurodegenerative diseases (NDs). 4-methyl-2,4-bis(4-hydroxyphenyl)pent-1-ene (MBP), which generated in the mammalian liver after BPA exposure, is a major active metabolite of BPA. MBP has been suggested to exert greater toxicity than BPA. However, the molecular mechanism of MBP on the neuronal cytotoxicity remains unclear. In this study, MBP exposure significantly reduced Neuro-2a cell viability and induced apoptotic events that MBP (5-15 mu M) exhibited greater neuronal cytotoxicity than BPA (50-100 mu M). The mitochondria-dependent apoptotic signals including the decrease in mitochondrial membrane potential (MMP) and the increase in cytosolic apoptosis-induced factor (AIF), cytochrome c release, and Bax protein expression were involved in MBP (10 mu M)-induced Neuro-2a cell death. Exposure of Neuro-2a cells to MBP (10 mu M) also triggered endoplasmic reticulum (ER) stress through the induction of several key molecules including glucose-regulated protein (GRP)78, C/EBP homologous protein (CHOP), X-box binding protein (XBP)-1, protein kinase R-like ER kinase (PERK), eukaryotic initiation factor 2 alpha (eIF2 alpha), inositol-requiring enzyme(IRE)-1, activation transcription factor(AFT)4 and ATF6, and caspase-12. Pretreatment with 4-PBA (an ER stress inhibitor) and specific siRNAs for GRP78, CHOP, and XBP-1 significantly suppressed the expression of these ER stress-related proteins and the activation of caspase-12/-3/-7 in MBP-exposed Neuro-2a cells. Furthermore, MBP (10 mu M) exposure dramatically increased the activation of extracellular regulated protein (ERK)1/2 and decreased Akt phosphorylation. Pretreatment with PD98059 (an ERK1/2 inhibitor) and transfection with the overexpression of activation of Akt1 (myr-Akt1) effectively suppressed MBP-induced

摘要： Primary Sjogren's syndrome (pSS) is an autoimmune disease that invades lacrimal glands, salivary glands, and other exocrine glands, but its pathogenic mechanism is still unclear. CD4(+)CD8(+) double-positive T (DPT) cells have been discovered in recent years to play an important role in autoimmune diseases and viral infections, but the frequency and significance of DPT in primary Sjogren's syndrome are still unclear. This study detected the frequency of DPT in the peripheral blood of patients with pSS and detected the clinical indicators and cytokines in patients. We then analyzed the correlation between DPT and clinical indicators, cytokines, and disease activity scores. The results showed that the peripheral DPT frequency of pSS patients was significantly higher than that of healthy controls. The peripheral DPT frequency was negatively correlated with ESR, IgA, and IgG, and peripheral DPT frequency was positively correlated with anti-inflammatory cytokine IL-10. Analysis of DPT and pSS disease activity scores found that DPT frequency had a negative correlation with ESSDAI and SSDAI. This study suggests that peripheral DPT may play a protective role in pSS. The frequency of peripheral DPT cells can be used as an indicator for disease activity. Regulating the expression of peripheral DPT cells is expected to become a new strategy for treatment of pSS.

关键词： Object detection   Feature extraction   Satellites   Neural networks   Automobiles   Sensors   Deep learning   Deep learning   faster R-CNN   neural networks   object classification   satellite images   vehicle detection   YOLO   Darknet  

摘要： Object detection and classification is important for video surveillance applications. Counting vehicles like cars, truck and vans is useful for intelligent transportation systems to identify dense and sparse roads, track loaded vehicles at the country borders. Even though many solutions such as appearance-based (Multi-block Local Binary Pattern) and model-based ((DATMO) algorithm) are proposed to classify the moving objects within the satellite images using machine learning and deep learning techniques, they either have over fitting problems or low performance. Hence these challenges have to be addressed during detecting and classifying the objects. Instead of training the classifiers with hand-crafted features, this paper uses neural network based object detection and classification to achieve promising accuracy better than the humans. Invariant feature concept is added to the existing Darknet Architecture of You Only Look Once (YOLO) and is combined with Faster Region-Based Convolutional Neural Networks (Faster R-CNN) to count the number of vehicles with different spatial locations. This combined model improves feature extraction step and vehicle classification process. The proposed system is tested on two benchmark datasets Cars Overhead with Context (COWC) and Vehicle Detection in Aerial Imagery (VEDAI) for counting the cars and trucks. Experimental results prove that the proposed system is better by 9% in detecting smaller objects than existing works.